Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
For millions of Americans, the ability to effectively use their hands is limited due to neurological or musculoskeletal diseases. Upper extremity dysfunction is prevalent among people with central nervous system disorders, which can be acquired, congenital, or degenerative in nature. For example, over 6 million Americans are stroke survivors, and even highly recovered stroke survivors have significant residual disability in hand function impacting the ability to perform basic and instrumental activities of daily living. Approximately 200,000 Americans have cerebral palsy, with impairments of the upper extremities among the most common features. Multiple sclerosis and Parkinson's disease, which are degenerative neurologic conditions, affect over a quarter of a million Americans each.
Upper extremity symptoms are common in these disorders, as well. For example, nearly 70% of people with Parkinson's disease experience initial symptoms that affect the upper extremities. Injuries affecting the peripheral nervous system can also impact upper extremity function. Over half a million Americans are estimated to have upper extremity amputations, and peripheral neuropathy affects a quarter of adults aged 65 and older, with increasing prevalence with age. Finally, diseases of the musculoskeletal can affect upper extremity function. For example, it is estimated that over 13 million Americans have symptomatic hand osteoarthritis.
Devices that enable improved functioning for individuals with limited hand use could significantly impact a large proportion of the population. For example, consider the difference between a mouse that can act on an exact pixel versus the experience of a finger touching perhaps hundreds of pixels on a touch-enabled device, such as a touch-based smartphone or tablet. Yet in playing a popular touch-enabled game, the touch-enabled device can use touches alone to determine a precise angle for a ballistic calculation and a precise time to release a projectile.
Gestures can be used as control inputs for human computer interaction. Typical gesture-based systems try to decode the full gesture being performed by the user. This has a direct natural learning curve for the person, as they perform hand or body gestures and the device does the heavy lifting to compute the motion. However, decoding gestures is technically complex, often requiring a relatively large number of electromyography (EMG) electrodes. Further, gestures may not map directly to the input signals used by mobile devices. Additionally, gestures are not common across populations of users with varying degrees of motor ability.